Novel virtual reality based training system for fine motor skills: Towards developing a robotic surgery training system

Abstract

Background: Training surgeons to use surgical robots are becoming part of surgical training curricula. We propose a novel method of training fine-motor skills such as Microscopic Selection Task (MST) for robot-assisted surgery using virtual reality (VR) with objective quantification of performance. We also introduce vibrotactile feedback (VTFB) to study its impact on training performance.

Methods: We use a VR-based environment to perform MST with varying degrees of difficulties. Using a well-known human-computer interaction paradigm and incorporating VTFB, we quantify the performance: speed, precision and accuracy.

Results: MST with VTFB showed statistically significant improvement in performance metrics leading to faster completion of MST with higher precision and accuracy compared to that without VTFB.

Discussion: The addition of VTFB to VR-based training for robot-assisted surgeries may improve performance outcomes in real robotic surgery. VTFB, along with proposed performance metrics, can be used in training curricula for robot-assisted surgeries.

Keywords: human-computer interaction; psychomotor; surgical robot; true positive rate; vibrotactile feedback.